Description:

You will be responsible for end-to-end data science cycles, encompassing designing, training, implementing, evaluating, and monitoring machine learning models.
You will design and implement highly scalable tools and algorithms based on state-of-the-art Machine Learning and Deep Learning methodologies.
The role involves working across the ML stack, from researching models, working with large datasets, training, and tuning existing models to creating new models, deploying them at scale, analyzing results, and presenting findings to stakeholders across tech and business domains.
You will develop and implement advanced predictive models to optimize customer experiences and other business outcomes.
The position requires analyzing large and complex datasets to extract actionable insights and drive business decisions.
You will interpret results and provide actionable insights to guide real-time decision-making within the business context.
Collaboration with cross-functional teams is essential to ensure proper deployment and integration of ML models for new releases.

Requirements:

A Bachelor's degree in data science, statistics, or computer science is a MUST.
You should have 3-4+ years of experience in data science or machine learning.
Strong experience in at least one of the following areas is required: Vision models or NLP models (Experience in Arabic NLP is a huge plus).
Proficiency in Python, TensorFlow, Keras, and PyTorch is necessary.
Good experience in SQL and non-relational databases is required.
Experience in data analytics reports generation and ML model development deployment is essential.

The position offers the opportunity to work remotely and full-time.
You will have the chance to collaborate with technical and non-technical business partners, enhancing your professional network.
There is an emphasis on continuous learning and development, with opportunities to mentor and support mid-level and junior developers.
You will be involved in overseeing interactions with vendors and third-party service providers, facilitating smooth collaboration and decision-making processes.
The role encourages staying updated on the latest research and learning new applications, tools, and technologies in the fields of data science and machine learning.